/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.zhaohg.spark.examples.ml;

import org.apache.spark.ml.feature.NGram;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.RowFactory;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.types.DataTypes;
import org.apache.spark.sql.types.Metadata;
import org.apache.spark.sql.types.StructField;
import org.apache.spark.sql.types.StructType;

import java.util.Arrays;
import java.util.List;

// $example on$
// $example off$

public class JavaNGramExample {
    public static void main(String[] args) {
        SparkSession spark = SparkSession
                .builder()
                .appName("JavaNGramExample")
                .getOrCreate();

        // $example on$
        List<Row> data = Arrays.asList(
                RowFactory.create(0, Arrays.asList("Hi", "I", "heard", "about", "Spark")),
                RowFactory.create(1, Arrays.asList("I", "wish", "Java", "could", "use", "case", "classes")),
                RowFactory.create(2, Arrays.asList("Logistic", "regression", "models", "are", "neat"))
        );

        StructType schema = new StructType(new StructField[]{
                new StructField("id", DataTypes.IntegerType, false, Metadata.empty()),
                new StructField(
                        "words", DataTypes.createArrayType(DataTypes.StringType), false, Metadata.empty())
        });

        Dataset<Row> wordDataFrame = spark.createDataFrame(data, schema);

        NGram ngramTransformer = new NGram().setN(2).setInputCol("words").setOutputCol("ngrams");

        Dataset<Row> ngramDataFrame = ngramTransformer.transform(wordDataFrame);
        ngramDataFrame.select("ngrams").show(false);
        // $example off$

        spark.stop();
    }
}
